High-performance computing may not be Ruby’s strength on the surface, but there is a great number of gems and third party packages which are often overlooked when it comes to this topic. We will assume no prior knowledge of PageRank (Google’s ranking algorithm) and will walk through the basic theory and computational challenges behind it. Along the way, we will look at a hands on example of computing PageRank for a 1-million page web, and the tools behind it:

Ruby GSL – Working with GNU Scientific Library

Linalg – Ruby Linear Algebra

NArray – Numerical Ruby

And others…

As a bonus, you’ll find that the ideas behind PageRank are surprisingly simple and powerful (no math-wiz certification required) and can be easily applied to many existing social and content networks – better recommendations, search, and discovery.

People planning to attend this session also want to see:

Ilya Grigorik

Google

Ilya Grigorik is the founder and CTO of AideRSS, a social engagement monitoring and analytics platform. He has been active in the Ruby and cloud computing community for the last three years, documenting and sharing hands on knowledge and experience with the latest architecture, design patterns, and FOSS projects (blog: www.igvita.com, twitter: @igrigorik). He is an active speaker at many Ruby and Cloud Computing events.